Metadata-Version: 2.4
Name: scisoftdev-tmp-HiPOP
Version: 1.0.9
Summary: High Performance Optimal Path module
Keywords: graph,graph-theory,shortest-path,dijkstra
License-Expression: LGPL-3.0-only
License-File: LICENSE
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Project-URL: Repository, https://github.com/EMob-Lab/HiPOP
Project-URL: Issues, https://github.com/EMob-Lab/HiPOP/issues
Requires-Python: >=3.10
Description-Content-Type: text/markdown

# HiPOP
High Performance Optimal Path module

## Install Hipop

HiPOP is the C++ graph library used by [MnMS](https://github.com/EMob-Lab/MnMS.git). 
You must have `CMake` and `make` installed on your computer.

## WARNING
If you are using MacOS ARM64, install the openmp library using Homebrew:
```shell
brew install libomp
```

### C++ only

Inside your conda environment go to the cpp folder, and install the code using cmake:

```shell
cd cpp
mkdir build
cd build
cmake .. -DCMAKE_PREFIX_PATH=<PREFIX>\
         -DCMAKE_INSTALL_PREFIX=<PREFIX>\
         -DCMAKE_BUILD_TYPE=Release\
         -DBUILD_TESTS=ON
cmake --build . --target install --config Release
```
Where `<PREFIX>` is the path to your prefix.

If you used conda to install the dependencies, replace it by `$CONDA_PREFIX`.

If you used venv to install the dependencies, replace it by the path to your venv.

You can then lauch the tests in the `build` directory:

```shell
ctest --output-on-failure
```


### Python

To install C++ code use the script `install_cpp.py`:

```shell
python python/install_cpp.py   
```

Then install the python lib:
```shell
python -m pip install python/
```
